LEADER 01667nam  2200397z- 450 
001 9910346706003321
005 20210211
010   $a1000039083
035   $a(CKB)4920000000094634
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/49634
035   $a(oapen)doab49634
035   $a(EXLCZ)994920000000094634
100   $a20202102d2014      |y         0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aHuman Pose Estimation with Implicit Shape Models
210   $cKIT Scientific Publishing$d2014
215   $a1 online resource (XVIII, 264 p. p.)
225 1 $aSchriftenreihe Automatische Sichtprüfung und Bildverarbeitung
311 08$a3-7315-0184-8 
330   $aThis work presents a new approach for estimating 3D human poses based on monocular camera information only. For this, the Implicit Shape Model is augmented by new voting strategies that allow to localize 2D anatomical landmarks in the image. The actual 3D pose estimation is then formulated as a Particle Swarm Optimization (PSO) where projected 3D pose hypotheses are compared with the generated landmark vote distributions.
610   $aaction recognition
610   $aAktionserkennungScene understanding
610   $aBildverarbeitung
610   $aComputer vision
610   $aHuman pose estimation
610   $aMenschliche Posenscha?tzung
610   $aSzenenverstehen
700   $aBrauer$b Jürgen$4auth$0480178
906   $aBOOK
912   $a9910346706003321
996   $aHuman Pose Estimation with Implicit Shape Models$93038231
997   $aUNINA